A GENETIC ALGORITHM BY USE OF VIRUS EVOLUTIONARY THEORY FOR SCHEDULING PROBLEM
Susumu Saito · 한국시뮬레이션학회 학술대회 논문집 · 2001
The genetic algorithm that simulates the virus evolutionary theory has been developed applying to combinatorial optimization problems. The algorithm in this study uses only one individual and a population of viruses. The individual is attacked, infected and improved by the viruses. The viruses are composed of four genes (a pair of top gene and a pair of tail gene). If the individual is improved by the attacking, the infection occurs. After the infection, the tail genes are mutated. If the same virus attacks several times and fails to infect, the top genes of the virus are mutated. By this mutation, the individual can be improved effectively. In addition, the influence of the immunologic mechanism on evolution is simulated.